Street lamp intelligent energy-saving method based on random forest regression prediction algorithm

A random forest and regression prediction technology, applied in energy-saving control technology, lamp circuit layout, lighting devices, etc., can solve the problem of unnecessary maintaining high illuminance, and achieve the goal of being conducive to adjustment and control, authoritative output results, and fast training speed. Effect

Inactive Publication Date: 2018-05-01
南京兆钧信息科技有限公司
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Problems solved by technology

However, after 10:00 p.m. in many small and medium-sized cities in our country, and after 12:00 p.m. in large cities, there are almost no vehicles and pedestrians in some non-busy streets. It is obviously unnecessar

Method used

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  • Street lamp intelligent energy-saving method based on random forest regression prediction algorithm
  • Street lamp intelligent energy-saving method based on random forest regression prediction algorithm
  • Street lamp intelligent energy-saving method based on random forest regression prediction algorithm

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Embodiment Construction

[0035] Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0036] see figure 1 , figure 2, is a schematic diagram of random forest model training and a specific flow chart of the smart energy-saving method for street lights based on the random forest regression prediction algorithm of the present invention. The core of the method is to train a random forest regression prediction model. Firstly, data is collected through the intelligent lighting system equipment, including the characteristics of human flow, traffic flow, sound, visible light, infrared, longitude and latitude, altitude, time, etc., and through a large amount of data analysis, the optimal power value that meets the lighting needs under this condition is obtained. These data are used as original data and divided into training set and test set. Environmental variables and other characteristics are used as independent variable X, and the best powe...

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Abstract

The invention discloses a street lamp intelligent energy-saving method based on random forest regression prediction algorithm. An intelligent street lamp system obtains original data information, likevisitors flow rate, vehicle flow rate, sound, visible light, infrared rays, latitude and longitude, altitude, etc. Through a large amount of data analysis, the optimum illumination (measured by power) meeting the demand of illumination under the condition can be obtained. The random forest regression prediction algorithm is made, wherein the series of data obtained by the system can be used as independent variable X, the corresponding power values can be set as dependent variable Y, and the random forest training conducts interpretation on Y through X, obtaining the random forest regression prediction model. The model is applied in the intelligent street lamp system, and the street lamp power can be intelligently controlled based on the circumferential environment condition of each streetlamp. The invention is advantageous in that with the advantages of the random forest algorithm, the method not only greatly increases the power prediction accuracy of the system, but also has the energy-saving effect under the condition that illumination is met.

Description

technical field [0001] The invention relates to an energy-saving method for street lamps, in particular to an intelligent power control method for street lamps based on a random forest regression prediction algorithm. Background technique [0002] Urban street lamps are an important aspect of my country's power consumption. With the increasingly tense energy supply, the call for energy saving is getting louder and louder. With the advancement of the "green lighting project", the development trend of lighting design and lighting products in China is facing a "green revolution". It will take saving energy and resources, protecting the earth's ecological environment, improving lighting quality, and improving comfort and health as its development goals. At present, lighting power consumption accounts for about 15% of the country's total power consumption, and many cities have begun to explore energy-saving work for street lamps. [0003] At present, the main energy-saving tech...

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Application Information

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IPC IPC(8): H05B37/02
CPCH05B47/10Y02B20/40
Inventor 叶玲张永军
Owner 南京兆钧信息科技有限公司
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